Systematic Analysis Research Articles

Calcimimetics or parathyroidectomy for kidney transplant recipients: is there still a question? a systematic review, meta-analysis and trial sequential analysis.

Secondary hyperparathyroidism is one of the most common complications of chronic kidney disease. The optimal treatment for chronic kidney disease nowadays is kidney transplant. Nonetheless, hyperparathyroidism does not always resolve after transplantation leading to tertiary hyperparathyroidism. The management of tertiary hyperparathyroidism can be either medical (calcimimetics) or surgical (parathyroidectomy). The aim of this study is to compare the medical and surgical treatment in terms of control of hyperparathyroidism and long-term implications on kidney graft function. We carried out a systematic review and meta-analysis of relevant studies up to March 2024 on MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Scopus databases. We compared the parathyroid hormone, calcium, creatinine and estimated glomerular filtration rate between the groups of patients that were treated with parathyroidectomy and those that were treated with calcimimetcs. Subsequently, we performed a trial sequential analysis to corroborate our findings. Four studies were included in the final analysis with a total number of 247 patients. Parathyroidectomy resulted in a greater decrease in parathyroid hormone and calcium levels (WMD 149.37, CI 95% 126.81-171.93, p < 0.0001 and WMD 0.7, CI 95% 0.45-0.96, p < 0.0001 respectively) but there was no difference between the surgical and medical management groups in the creatinine and eGFR levels (CI 95%, -0.62-0.17, p = 0.27 and CI 95%, -8.06 - 20.54 p = 0.39). The trial sequential analysis corroborated these findings. Parathyroidectomy is more effective in controlling hyperparathyroidism in kidney transplant recipients, as it leads to a greater decrease in parathyroid hormone and calcium levels. However, there is no difference in the long-term function of the kidney graft, as the creatinine and estimated glomerular filtration values were similar in the surgical and medical management groups.

Comprehensive analysis of α2,3-sialyltransferases as prognostic biomarkers and immunotherapy targets in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC), a therapy-resistant aggressive kidney cancer, exhibits resistance to immune checkpoint inhibitors. Altered sialylation is involved in tumor development, affecting immune microenvironment dynamics. In the study, through systematic bioinformatics analysis and experimental verification, we demonstrated that ST3Gal5 expression was elevated in tumor tissues of KIRC patients, correlating with poor prognosis, and ST3Gal1 was downregulated and associated with a better prognosis. Immunohistochemistry analysis confirmed the expression patterns of ST3Gal1 and ST3Gal5 in 30 KIRC patients. Furthermore, KIRC patients were stratified into two clusters based on ST3Gal1 and ST3Gal5 levels using consensus clustering to investigate their roles in KIRC tumorigenesis, immune characteristics and treatment sensitivity. KIRC patients in Cluster 2, characterized by increased ST3Gal5 and downregulated ST3Gal1 expression, exhibited increased expression of immune checkpoints, immune cell infiltration, immune escape scores, and worse prognosis. Knockdown of ST3Gal5 in KIRC cell lines (786-O and 769-P) resulted in reduced tumor proliferation, migration, and invasion in vivo and in vitro. Together, the dysregulation of sialyltransferases (ST3Gal1 and ST3Gal5) in KIRC influences tumorigenesis and immune responses. These findings underscore the potential of ST3Gal1 and ST3Gal5 as prognostic factors and immunotherapy targets for KIRC.

Cannabis use and HIV among Black sexually minoritized men: a systematic review and narrative analysis.

We conducted a systematic review evaluating the extant literature examining the impacts of cannabis use on HIV-related outcomes among Black sexual minoritized men (BSMM). Systematic review. We conducted a search in November 2024 of PubMed, EMBASE, CINAHL, PsycINFO, and Web of Science using keywords related to BSMM, HIV, and cannabis. Study quality was assessed utilizing a tool developed for observational studies. 108 unique articles were screened with 55 undergoing full-text review, and 20 met inclusion criteria. Results were synthesized and presented utilizing a narrative review process. We identified 20 studies published between 1999-2024. Measures of cannabis use included any use (e.g., ever, past 30 days), daily/intermittent/heavy use, use before/during sex, and problematic use. Outcomes included: HIV positivity/seroconversion, HIV Continuum of Care (CoC), PrEP CoC, and sex behavior strengths, vulnerabilities, and assets. Study findings were generally mixed, however positive associations between cannabis use and HIV seroconversion, inconsistent condom use, being HIV-positive and unaware of one's serostatus, and suboptimal ART adherence were reported. This systematic review identified a growing literature on cannabis use and HIV among Black SMM. Conclusions that can be drawn from the evidence are limited. There is a critical need for studies that more rigorously measure cannabis use by considering contexts of cannabis use. In addition, there is a need for research that examines the pathways and mechanisms through which cannabis use may affect prevention and treatments outcomes related to HIV among Black SMM.

Models based on dietary nutrients predicting all-cause and cardiovascular mortality in people with diabetes

Dietary intervention plays a vital role in improving the prognosis of people with diabetes mellitus (DM). Currently, there is a lack of systematic analysis of the relation between dietary nutrients and long-term mortality risk in people with DM. The study aims to establish models predicting long-term mortality and explore dietary nutrients associated with reduced long-term events to guide daily dietary decisions in people with DM. The retrospective cohort study collected 5060 participants with DM from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. The least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithm were applied to identify key mortality-related dietary factors, which were subsequently incorporated into risk prediction nomogram models. The receiver operating characteristic (ROC) curve, calibration plot and decision curve analysis (DCA) were utilized to evaluate the performance of the models. The association of key dietary nutrients with all-cause and cardiovascular mortality were visualized by restricted cubic spline (RCS) models both in the whole and subgroups by sex, age, drinking and smoking status. The overall median age of the cohort was 62.0 years (interquartile range (IQR) 52.0–70.0), 2564 (50.67%) being male. During a median follow-up period of 56.0 months, 997 (19.70%) all-cause deaths were recorded, with 219 (21.97%) of which being ascribed to cardiovascular disease. The nomogram models based on key dietary nutrients identified by LASSO and RF demonstrated a significant predicative value for all-cause and cardiovascular mortality. Dietary fiber and magnesium were the common predictive nutrients in the two nomogram models. The RCS curve revealed that dietary fiber and magnesium were negatively associated with long-term mortality in the whole and subgroups of people with DM after adjustment of potential confounders. The diet of people with DM is closely associated with mortality. The nomogram models based on dietary nutrients can predict long-term mortality of people with DM, and the higher intake of dietary fiber and magnesium was associated with reduced risks of both long-term all-cause and cardiovascular mortality.

Systematic analysis of the pharmacogenomics landscape towards clinical implementation of precision therapeutics in Greece

Pharmacogenomics (PGx) aims to delineate a patient’s genetic profile with differences in drug efficacy and/or toxicity, particularly focusing on genes encoding for drug-metabolizing enzymes and transporters. Clinical implementation of PGx is a complex undertaking involving a multidisciplinary approach that includes, among others, a thorough understanding of a country’s preparedness to adopt this modern discipline and a detailed knowledge of PGx biomarkers allelic spectrum at a population level. In several European populations, particularly in countries with lower income, clinical implementation of PGx is still in its infancy. We have previously performed a pilot study to determine the prevalence of PGx biomarkers in 18 European populations, as the first step towards population PGx at the European level. Here, we provide a comprehensive analysis of the current state of PGx in Greece, including a detailed allelic frequency spectrum of clinically actionable PGx biomarkers, the level of PGx education in academia, the provision of PGx testing services from public and private laboratories, and the aspects of the regulatory PGx environment, especially with respect to the discrepancies between the Greek National Organization of Medicines and the European Medicine Agency and health technology assessment. This study would not only provide the foundations for expediting the adoption of PGx in clinical reality in Greece but can also serve as a paradigm for replicating future studies in other European countries, to expand on previously available pilot studies.

Addressing selection bias while estimating aggregate development effectiveness: can we obtain externally valid estimates at portfolio level?

ABSTRACT As a result of greater demand from funders and governing bodies to assess their ‘impact for money’, the need for aggregate aid effectiveness for development agencies has become increasingly prominent. Measurement of aid effectiveness or corporate impact, however, requires attribution, i.e. the capacity to causally attribute observed impacts from an investment project to the project alone, as well as counterfactual-based impact evaluations. As the prevalence of impact evaluations grows among development agencies, attributable aggregate development effectiveness to measure institution-wide results is a necessary component of any institution’s impact evaluation agenda to ensure accountability, identify performance gaps, and areas for improvement. ‘Intelligent’ aggregation additionally requires three key elements, namely a critical mass of impact evaluations representing the investment portfolio of the agency in question, a methodology for aggregation, and a universe of projects from where the projects evaluated were randomly drawn. In this paper, a novel methodology based on meta-analytic techniques, selection models and projection methods is proposed along with a number of systematic analyses that adjust for the possible presence of selection bias, a crucial factor to take into account while estimating aggregate development effectiveness.

Recurrence of herpetic keratouveitis following cataract surgery.

Herpetic eye disease (HED) is a leading cause of infectious vision loss worldwide. Cataract surgery is known to be implicated in triggering the recurrence of herpes keratouveitis. This study evaluates the current evidence on the association between HED and cataract surgery, focusing on the risk factors and potential pathogenic mechanisms and preventive strategies involved with reactivation or new-onset herpes-related keratitis, uveitis, or keratouveitis. A comprehensive search of databases (Cinahl, Embase, Scopus, ProQuest, Web of Science, and PubMed) was conducted to identify articles describing the association between new onset or reactivation of HED after cataract surgery up to March 2024. A total of 24 studies were included. The heterogeneity of the studies precluded systematic analysis. However, the findings suggest that the herpetic recurrence rate, mainly in the form of keratitis, after cataract surgery is high (approximately 40%), mostly occurring ≤ 2years after surgery, and can be influenced by factors such as topical corticosteroids, the quiescent time before surgery, and history of prior recurrences, and the patient's comorbidities, including diabetes and atopy. The current evidence for prescribing perioperative HED prophylaxis is of inadequate quality. Available evidence suggests that herpetic recurrences tend to occur in the first two years after cataract surgery. A longer quiescent time before surgery might reduce the risk of recurrence. Prospective studies analyzing the effects of perioperative prophylaxis are needed.

Decision-Making by the Defense Party in Ukrainian Criminal Justice: Balancing Needs and Capabilities

Objective: The purpose of the article is to highlight the features of the decision-making process by the defense party in Ukrainian criminal proceedings and to identify the main needs and capabilities of the subjects involved. Theoretical Framework: This study is based on contemporary scholarly perspectives in the fields of criminal law and procedure, forensic science, and legal psychology, the provisions of current legislation and statistical data. Method: To explore decision-making process by the defense party, this study will use a range of general and specialized scientific research methods including systemic analysis, formal-legal, comparative, generalization, and modeling. Results and Discussion: The authors argue that defense decisions in criminal proceedings are non-law-applying and significantly differ from the decisions of the prosecution or the court. The study demonstrates that defense decisions are structurally composed of the intended goal, the informational foundation, and the available alternative courses of action. The decision-makers on behalf of the defense include the defendant, the defense attorney, and the legal representative, each of whom possesses their own set of procedural needs and capabilities. It is emphasized that the most effective decisions are those made by the defendant in collaboration with defense attorney. Contributions: The significance of the research results lies in their potential to serve as a foundation for developing practice-oriented recommendations on optimizing defense strategy against criminal charges, and formulating recommendations to overcome unlawful resistance to pre-trial investigations and court proceedings by the defense side.

Global, regional, and national disease burden attributable to high systolic blood pressure in youth and young adults: 2021 Global Burden of Disease Study analysis

BackgroundHigh systolic blood pressure (HSBP) can cause adverse cardiovascular events and is therefore associated with a heavy global disease burden. However, this disease burden is poorly understood in youth and young adults. We aimed to explore this population to better understand the evolving trends in HSBP-related disease burden, which is crucial for effectively controlling and mitigating harmful effects.MethodsThis systematic analysis used data from the 2021 Global Burden of Disease Study, spanning 1990–2021. Participants were aged 15–39 years from 204 countries/territories. We analysed HSBP-related disease burden by region, sex, age, and temporal trends. The primary outcomes were disability-adjusted life years (DALYs), mortality rates, and estimated annual percentage change.ResultsGlobally, the number of HSBP-related deaths among youth and young adults has increased by 36.11% (95% uncertainty interval [95% UI], 20.96–52.37%), whereas the number of DALYs has increased by 37.68% (95% UI, 22.69–53.65%); however, global mortality and DALY rates have remained relatively stable. In 2021, the mortality and DALY rates were 4.29 (95% UI, 3.29–5.28) and 263.37 (95% UI, 201.40–324.46) per 100,000 population, respectively. The overall HSBP-related burden was higher in males than in females, with increasing and decreasing trends for males and females, respectively. Regionally, significant improvements in HSBP-related burden were observed in most high-sociodemographic index (SDI) regions, including high-income Asia Pacific (deaths: percentage change, − 72.65%; DALYs: percentage change, − 69.30%) and Western Europe (deaths: percentage change, − 72.89%; DALYs: percentage change, − 67.48%). In contrast, middle-SDI regions had the highest number of deaths and DALYs in 2021, whereas low-middle-SDI regions had the highest mortality and DALY rates. Furthermore, low-SDI regions experienced the largest increase in the number of deaths and DALYs. The HSBP-related burden increased with age; in addition, the proportion of deaths or DALYs due to ischaemic heart disease and stroke increased with age, reaching > 75% for those > 25 years of age.ConclusionsThe increase in global HSBP-related burden among youth and young adults indicates that current preventative efforts are insufficient. Therefore, targeted measures are needed to counter the trends in HSBP-related diseases and reduce disparities across regions and sexes.

Generative Artificial Intelligence and the Evolving Challenge of Deepfake Detection: A Systematic Analysis

Deepfake technology, which employs advanced generative artificial intelligence to create hyper-realistic synthetic media, poses significant challenges across various sectors, including security, entertainment, and education. This literature review explores the evolution of deepfake generation methods, ranging from traditional techniques to state-of-the-art models such as generative adversarial networks and diffusion models. We navigate through the effectiveness and limitations of various detection approaches, including machine learning, forensic analysis, and hybrid techniques, while highlighting the critical importance of interpretability and real-time performance in detection systems. Furthermore, we discuss the ethical implications and regulatory considerations surrounding deepfake technology, emphasizing the need for comprehensive frameworks to mitigate risks associated with misinformation and manipulation. Through a systematic review of the existing literature, our aim is to identify research gaps and future directions for the development of robust, adaptable detection systems that can keep pace with rapid advancements in deepfake generation.

Integration of UAV Multispectral Remote Sensing and Random Forest for Full-Growth Stage Monitoring of Wheat Dynamics

Wheat is a key staple crop globally, essential for food security and sustainable agricultural development. The results of this study highlight how innovative monitoring techniques, such as UAV-based multispectral imaging, can significantly improve agricultural practices by providing precise, real-time data on crop growth. This study utilized unmanned aerial vehicle (UAV)-based remote sensing technology at the wheat experimental field of the Hebei Academy of Agriculture and Forestry Sciences to capture the dynamic growth characteristics of wheat using multispectral data, aiming to explore efficient and precise monitoring and management strategies for wheat. A UAV equipped with multispectral sensors was employed to collect high-resolution imagery at five critical growth stages of wheat: tillering, jointing, booting, flowering, and ripening. The data covered four key spectral bands: green (560 nm), red (650 nm), red-edge (730 nm), and near-infrared (840 nm). Combined with ground-truth measurements, such as chlorophyll content and plant height, 21 vegetation indices were analyzed for their nonlinear relationships with wheat growth parameters. Statistical analyses, including Pearson’s correlation and stepwise regression, were used to identify the most effective indices for monitoring wheat growth. The Normalized Difference Red-Edge Index (NDRE) and the Triangular Vegetation Index (TVI) were selected based on their superior performance in predicting wheat growth parameters, as demonstrated by their high correlation coefficients and predictive accuracy. A random forest model was developed to comprehensively evaluate the application potential of multispectral data in wheat growth monitoring. The results demonstrated that the NDRE and TVI indices were the most effective indices for monitoring wheat growth. The random forest model exhibited superior predictive accuracy, with a mean squared error (MSE) significantly lower than that of traditional regression models, particularly during the flowering and ripening stages, where the prediction error for plant height was less than 1.01 cm. Furthermore, dynamic analyses of UAV imagery effectively identified abnormal field areas, such as regions experiencing water stress or disease, providing a scientific basis for precision agricultural interventions. This study highlights the potential of UAV-based remote sensing technology in monitoring wheat growth, addressing the research gap in systematic full-cycle analysis of wheat. It also offers a novel technological pathway for optimizing agricultural resource management and improving crop yields. These findings are expected to advance intelligent agricultural production and accelerate the implementation of precision agriculture.

Communication with Disabled Fans at Sports Events: Approaches, Challenges, and Opportunities

This study investigates how effectively European football clubs communicate and implement accessibility features for disabled fans, aiming to develop a comprehensive framework for evaluating these practices. Using a multi-phase research design, the study analyzes disability support systems through semi-structured interviews with representatives from eleven European football clubs and a systematic analysis of club documentation. The methodology combined traditional qualitative analysis with large language model (LLM)-assisted content analysis, enabling robust identification of thematic patterns and performance indicators. Our findings reveal significant disparities in disability support practices, with larger clubs demonstrating structured approaches through dedicated Disability Access Officers (DAOs) and comprehensive communication strategies. Analysis identified three distinct performance tiers: Elite Performers, primarily well-resourced clubs with advanced systems; Solid Performers, mid-tier clubs with established frameworks; and Developing Systems, smaller organizations with emerging support structures. We present a validated Fan Communication Model incorporating key weighted criteria, including infrastructure, dedicated personnel, engagement, specific adaptations, ticketing, challenge management, and feedback systems. This model provides a standardized framework for evaluating disability support communication in football organizations. The research demonstrates the importance of integrating technological solutions with human-centered approaches while maintaining universal design principles. Our findings contribute to the sports accessibility literature and provide evidence-based recommendations for football organizations seeking to enhance their communication with disabled fans.

Mean Field Initialization of the Annealed Importance Sampling Algorithm for an Efficient Evaluation of the Partition Function Using Restricted Boltzmann Machines

Probabilistic models in physics often require the evaluation of normalized Boltzmann factors, which in turn implies the computation of the partition function Z. Obtaining the exact value of Z, though, becomes a forbiddingly expensive task as the system size increases. A possible way to tackle this problem is to use the Annealed Importance Sampling (AIS) algorithm, which provides a tool to stochastically estimate the partition function of the system. The nature of AIS allows for an efficient and parallel implementation in Restricted Boltzmann Machines (RBMs). In this work, we evaluate the partition function of magnetic spin and spin-like systems mapped into RBMs using AIS. So far, the standard application of the AIS algorithm starts from the uniform probability distribution and uses a large number of Monte Carlo steps to obtain reliable estimations of Z following an annealing process. We show that both the quality of the estimation and the cost of the computation can be significantly improved by using a properly selected mean-field starting probability distribution. We perform a systematic analysis of AIS in both small- and large-sized problems, and compare the results to exact values in problems where these are known. As a result, we propose two successful strategies that work well in all the problems analyzed. We conclude that these are good starting points to estimate the partition function with AIS with a relatively low computational cost. The procedures presented are not linked to any learning process, and therefore do not require a priori knowledge of a training dataset.

Systematic analysis and prediction of the burden of Alzheimer’s disease and other dementias caused by hyperglycemia

BackgroundAlzheimer’s disease and other dementias (ADOD) pose a significant and escalating global public health challenge, particularly among the aging populations. Emerging evidence has identified high fasting plasma glucose (HFPG) as a major modifiable risk factor for ADOD, linking impaired glucose metabolism to cognitive decline and neurodegeneration. Despite this association, the comprehensive impact of HFPG on the global burden of ADOD has not been fully elucidated. Understanding the extent to which HFPG contributes to ADOD is crucial for developing targeted interventions and optimizing healthcare resource allocation to address this growing concern.MethodsUsing Global Burden of Disease data (GBD 2021), we analyzed the global HFPG-related ADOD burden from 1990 to 2021 using an age-period-cohort framework and predicted trends for 2050. A Shiny platform was developed to visualize the disease burden and trends across 204 countries and regions.ResultsIn 2021, approximately 15% of ADOD deaths and disability-adjusted life years (DALYs) were attributed to HFPG, a 271.05% increase from 1990. The incidence rate rose from 47.07 to 66.42, indicating poor control. The mortality rate from HFPG-ADOD increased by 305.81%. The primary burden was among the 80–84 age group. Trends in ASDR and ASMR showed an increase across most SDI regions, except Low SDI. Decomposition analysis and the APC model indicated poor control in high SDI regions due to aging populations over the past 5 years. By 2050, the global prevalence is projected to reach 1,003,018.047 (26124.40377, 12114480.49), with 345,342.5738 (1431.57781, 6022119.213) males and 657,675.4731 (24692.82596, 6092361.28) females. The Shiny platform predicts a yearly increase in ASDR and ASMR for HFPG-ADOD in China, which is consistent with GBD platform trends. The platform is accessible at http://116.196.73.86:3838/GBD/HFPG-ADOD/.ConclusionThe global burden of HFPG-related ADOD has been increasing, even in high SDI regions, over the past 5 years and is expected to continue rising until 2050. Implementing appropriate health policies to mitigate this trend could significantly reduce the substantial burden caused by HFPG-induced ADOD. Promoting the use of the Shiny prediction platform will contribute significantly to global healthy aging.

Embracing opportunities and minimizing risks: leveraging decision models for project selection in Southeast Asian countries

In real estate investments in Southeast Asia, decisions worth billions of dollars are usually made without systematic analysis, leading to project failures. This paper presents a novel two-tier matrix method that combines the decision on country-project selection into a model. This model could assist real estate investors to select the right projects in Indonesia, Malaysia and Thailand, which is significantly under-reported. We used the Analytic Hierarchy Process (AHP) and the Weighted Sum Method (WSM) to create a matrix model to analyse investment projects. The results are encouraging and indicate that Malaysia is the best country for real estate investment, followed by Thailand and Indonesia respectively. This study also simulates the decision making of very experienced to inexperienced investors. It concluded that the two-tier decision model can safeguard investors from making intuitive decision mistakes and help them to make informed decisions when selecting investment projects in Southeast Asian countries.

Application Strategies of MXenes in Photodetector: Dual Perspectives of Acting as Modifiers and Being Modified

Photodetectors, as essential devices for photoelectric conversion, are critical to advancing military, industrial, and civil technologies. In the post‐Moore era, the demand for extreme miniaturization and multifunctionality has driven intense research into low‐dimensional materials. Two‐dimensional MXenes have attracted considerable attention due to their exceptional conductivity, controllable surface functional groups, and tunable bandgap associated with surface terminals. However, the lack of systematic analysis on how MXenes enhance photodetector performance, modification mechanisms, and the multifunctional applications of modified MXenes constrains progress in this field. Herein, this review focuses on the dual roles of MXenes as performance modifiers and modifiable materials in photodetectors. It systematically examines the preparation and modification strategies of MXenes. Emphasis is placed on their potential as conductive electrodes, carrier transport layers, and heterojunctions with photosensitive layers to optimize device performance. The impact of advanced modification techniques on MXene properties is also explored, along with their subsequent application in photodetectors with enhanced sensitivity and stability. Additionally, emerging opportunities for MXenes in enabling novel device architectures and multifunctional photodetection platforms are highlighted. Herein, strategic guidance is provided for photodetector structural design and material innovation and establishes a foundation for next‐generation optoelectronic devices and broader MXene integration in photonic technologies.

The education-to-work transition: a systematic analysis of pedagogical interventions in the context of higher education

ABSTRACT Higher education has implemented various pedagogical interventions to increase connectivity with the workplace and ease students’ education-to-work transition. However, the effectiveness and underlying mechanisms of these interventions in supporting students with this transition remains largely unexplained. The present review article analyzed 49 articles bringing together two theoretical frameworks on this transition: connectivity and boundary crossing. Results show that connectivity can be increased by collaborating with the workplace in several ways. However, our results also show that higher education seldom learns from this collaboration, resulting in a lack of effective boundary practices to support students in their education-to-work transition. On top of that, our research demonstrates the importance of assessing the effectiveness of any of these interventions from both a student and a labor economics perspective.

A systemic analysis of container terminal layouts

The paper provides a systemic analysis of the layout characteristics of a geodatabase comprised of a large sample of 331 global container terminals. Despite the propensity towards terminal standardization that can be expected from containerization, container terminals demonstrate a substantial diversity in measurable attributes such as perimeter, terminal surface, yard surface, and berth length. This is mainly attributed to site characteristics constraining terminal design and operations with clusters arranged along terminal rectangularity level. A further observation concerns the propensity of container terminals to be oriented longitudinally. Geographical factors remain important, including whether the terminal design is a reconversion of an older facility, an adaptation to specific site constraints, or a new land reclamation.

ANTIBIOTIC RESISTANCE: A GLOBAL THREAT AND PATHWAYS TO SOLUTIONS

Introduction. Antimicrobial resistance (AMR) represents a critical global health challenge that poses significant threats to public health, food security, and economic stability. AMR occurs when microorganisms such as bacteria, viruses, fungi, and parasites develop resistance to antimicrobial agents, rendering treatments ineffective and leading to persistent infections, higher medical costs, and increased mortality rates. This crisis is exacerbated by factors such as the overuse and misuse of antibiotics in healthcare and agriculture, insufficient regulation, inadequate infection control measures, and limited access to diagnostic tools. As AMR continues to evolve, its impact is felt worldwide, particularly in low- and middle-income countries where resources for combating this issue are often scarce. The growing burden of AMR underscores the urgency for global and regional collaborations, integrated surveillance systems, and the implementation of effective antimicrobial stewardship programs to mitigate its impact. Purpose of the review. This study aims to analyze AMR as a global threat, identify key factors driving its emergence and spread, evaluate existing mitigation strategies, and propose practical recommendations to enhance the effectiveness of AMR management at regional and global levels. Materials and methods: A systematic analysis was conducted using open-access articles published within the last five years from databases such as PubMed, Medline, Google Scholar, eLibrary, and CyberLeninka. Included studies met evidence levels A and B, comprising meta-analyses, systematic reviews, and cohort studies. Key areas of focus included epidemiological data, resistance patterns, and intervention effectiveness. Results: Between 1990 and 2021, AMR was responsible for over one million deaths globally each year, with significant increases in fatalities among individuals aged 70 and older. In 2021, bacterial AMR contributed to an estimated 4.71 million deaths globally, including 1.14 million directly attributable to AMR. Projections suggest AMR-related deaths could reach 10 million annually by 2050 if current trends continue. Factors such as unregulated antibiotic use, limited diagnostic resources, and the spread of multidrug resistance (MDR), extensive drug resistance (XDR), and pan-resistance (PDR) exacerbate the crisis. Regional disparities, particularly in Africa and Asia, emphasize the need for strengthened surveillance and regulatory measures. Conclusion. AMR is a growing global crisis that demands urgent action. Implementing genomic tools for AMR monitoring and adopting the «One Health» approach, which integrates human, animal, and environmental health, are essential to addressing this challenge. Strengthening regional monitoring, increasing public awareness, and fostering global collaborations are pivotal for sustainable AMR control. These measures are crucial to reducing mortality rates, optimizing healthcare outcomes, and mitigating the socioeconomic impacts of AMR.

Systematic and Quantitative Assessment of Reduced Model Resolution on the Transient Structural Response Under Wind Load

The wind-induced response of structures is typically studied in wind tunnels either on scaled models or using numerical approaches under similar transient load conditions. In early design phases—where the potential for impactful change is most significant—information is often limited. As a result, studies are frequently conducted on simplified or reduced-resolution structural models. Typical applications for dimensionally reduced engineering models include early design phases, deciding on the need for high-fidelity analyses, and verifying wind tunnel models, which are often constructed using beams with lumped masses. In this contribution, the validity of these approaches is tested. Various limitations intrinsically arising from such modeling assumptions, showcased on a generic high-rise under dynamic wind load conditions, are highlighted. The systematic parametric analysis focuses on the variations in transient structural responses, particularly displacement and accelerations at the top of a building. Various wind loading cases are studied, with the reduction of the resolution taking place either in the original or in modal space. Results indicate that a considerable reduction is possible, but characteristic design values tend to deteriorate in cases of a high reduction, particularly when higher mode contributions are truncated. It is observed that the top-floor acceleration and displacement can be captured with considerable accuracy with three lumped masses for tall buildings. It is critical to study the impact of simplifying models starting at the highest level of detail possible. Here, a three-DoF model was able to capture the displacement up to a deviation of 11 % and accelerations up to 20%. These approximate models are useful for initial design stages, optimization, uncertainty quantification, etc., where fast, cheap, and moderately accurate model evaluations are necessary.